Contingent movement and cooperation evolve under generalized reciprocity
Bibliographic record
Abstract
How cooperation and altruism among non-relatives can persist in the face of cheating remains a key puzzle in evolutionary biology. Although mechanisms such as direct and indirect reciprocity and limited movement have been put forward to explain such cooperation, they cannot explain cooperation among unfamiliar, highly mobile individuals. Here we show that cooperation may be evolutionarily stable if decisions taken to cooperate and to change group membership are both dependent on anonymous social experience (generalized reciprocity). We find that a win-stay, lose-shift rule (where shifting is either moving away from the group or changing tactics within the group after receiving defection) evolves in evolutionary simulations when group leaving is moderately costly (i.e. the current payoff to being alone is low, but still higher than that in a mutually defecting group, and new groups are rarely encountered). This leads to the establishment of widespread cooperation in the population. If the costs of group leaving are reduced, a similar group-leaving rule evolves in association with cooperation in pairs and exploitation of larger anonymous groups. We emphasize that mechanisms of assortment within populations are often behavioural decisions and should not be considered independently of the evolution of cooperation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".